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Postdoc: Geospatial AI Modelling & Uncertainty Quantification of Biomass Faculty: Faculty of Geosciences Department: Department of Physical Geography Hours per week: 32 to 40 Application deadline
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dimension of uncertainty in power system operations, necessitating more complex and adaptive decision-making processes for system operators. While some prototypical power system optimization problems have
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uncertainties about viable business models and reward structures. Your job This postdoctoral position is part of ReGeNL , a large national inter- and transdisciplinary research programme aimed at accelerating
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an understanding of how humans respond to the uncertainty and risk that they bring. From the agent’s perspective, actions are taken to bring itself into safety if there are uncertainties, but this may introduce new
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Today, companies across a wide range of industries face the challenge of managing increasingly complex stochastic systems, where uncertainty is inherent and data is abundant. These systems arise in
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PhD candidates and close to 3000 BSc and MSc students apply aerospace engineering disciplines to address the global societal challenges that threaten us today, climate change without doubt being
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hampered by uncertainties about viable business models and reward structures. Your job This postdoctoral position is part of ReGeNL , a large national inter- and transdisciplinary research programme aimed
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the context of the Energy Transition. Transitioning to a power system heavily reliant on weather-dependent renewable energy to achieve environmental targets introduces a critical dimension of uncertainty in
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, onboard AI, explainable AI (xAI), and uncertainty quantification, can unlock new insights for environmental sustainability and climate resilience. For example, AI-driven methodologies might be deployed
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suitable for aircraft integration. To address this uncertainty, MODABAT adopts a modular, scalable, and technology-open battery system design approach, ensuring adaptability to the ambitious timeline and the